Making and maintaining neighbourhood connections when living alone with dementia
Bibliographic record
Abstract
Introduction This chapter draws on qualitative research using participatory methods to explore the experience of people with dementia who live alone. Drawing on data gathered in Sweden and the UK, the chapter highlights the distinct challenges of living alone with dementia and explores the different ways that people remain connected to neighbourhood places. We argue that the invisibility of such experiences to dementia policy and strategies (which typically assume the presence of a cohabiting carer or household member to provide support) needs to be addressed if dementia-friendly initiatives are to be truly inclusive. Demographic projections show that the number of people living in single households will continue to increase steadily in many western and northern European countries and that older women are the fastest-growing section of the single householder population (Sundström et al, 2016; United Nations, 2017). The ageing population living alone in Europe also includes an increasing proportion of people with dementia (Prescop et al, 1999; Gaymu and Springer, 2010; Prince et al, 2015). In Canada, France, Germany, the UK and Sweden, between one third and one half of the population of people with dementia residing in a neighbourhood context live in single households (Ebly et al, 1999; Nourhashemi et al, 2005; Alzheimer's Society, 2013; Eichler et al, 2016; Odzakovic et al, 2019). Despite this increase in single householders with dementia, there is currently limited awareness of the particular challenges associated with living alone with dementia, even within emerging discourses and practices associated with dementia-friendly communities (Alzheimer's Society, 2013; Age UK, 2018; Odzakovic et al, 2018). As such, there is a danger that the creation of ‘dementia-friendly’ communities, and especially those based on communities of place, may rest upon a series of normative assumptions about dementia and about the relational context of people living with the condition. Evidence from service-oriented research shows that people with dementia who live alone are more prone to (unplanned) hospitalisation (Ennis et al, 2014); are at greater risk of malnutrition (Nourhashemi et al, 2005); are likely to be admitted to long-term care at an earlier point in their journey with dementia (Yaffe et al, 2002); are often less well connected to formal services (Webber et al, 1994); and lack the advocacy of a co-resident carer (Eichler et al, 2016).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".